@inproceedings{007b344ec0e442feb565d47cebb95922,
title = "It is probably me: A Bayesian approach to weighting digital identity sources",
abstract = "As human-kind becomes increasingly dependent on online services to conduct the fundamental aspects of daily life, digital footprints and the associated online service digital identities have the capacity to provide verification that an individual is a 'real person' and possesses a true identity. A recognized challenge in utlising this data in this manner is that different types of online services possess different levels of reliability. This paper explores the application of na{\"i}ve Bayes theorem to subsets of attributes contained within various types of online accounts that are presented as 'identity sources'. This seeks to demonstrate that less reliable sources such as social media accounts will produce lower trust scores than more reliable sources following application of Bayes theorem. The results for which will be used to determine if digital identity sources can be relied upon in place of traditional paper identification documentation. This research and testing has been conducted as an element of a larger intelligent identity authentication system that seeks to create a solution that proves an identity is genuine via an individual's digital footprint.",
keywords = "Authentication, Digital Footprint, Identification, Identity, Trust",
author = "Juanita Blue and Joan Condell and Tom Lunney",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 International Symposium on Networks, Computers and Communications, ISNCC 2019 ; Conference date: 18-06-2019 Through 20-06-2019",
year = "2019",
month = jun,
doi = "10.1109/ISNCC.2019.8909201",
language = "English",
series = "2019 International Symposium on Networks, Computers and Communications, ISNCC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 International Symposium on Networks, Computers and Communications, ISNCC 2019",
}